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Evidence row 565000

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 7c6a218d-d2e6-4b3a-922c-0b10ea42a6ee
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
f4c0a255fbe4e59525ba95fa5824b67c1a8e7f2eb1283f509a9d541a72fdd3f9
Leaf
0x08a66ac8e1ef7cf10407841d1c97cc9d2af4c2825c9916fa00f92b68f084f1cf

What was observed

{
  "count": 3,
  "tools": [
    {
      "description": "Free. Fetches a URL and reports how readable it is to AI assistants and agents: whether GPTBot, ClaudeBot, PerplexityBot, Google-Extended and friends are allowed in robots.txt, how much real text survives without JavaScript, what JSON-LD entity types are declared, and whether llms.txt, sitemap.xml and an A2A agent card exist. Returns a score, the individual checks, and concrete fixes. It does NOT tell you whether assistants actually recommend the brand — that requires querying the models, which is the paid audit.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "url": {
            "description": "The site to check, e.g. example.com or https://example.com/pricing",
            "type": "string"
          }
        },
        "required": [
          "url"
        ],
        "type": "object"
      },
      "name": "audit_ai_readiness"
    },
    {
      "description": "Free. Returns the agentbuilt catalog of pay-per-result data tools for AI pipelines — what each one does, when to use it, what it explicitly cannot do, and what it costs. Use this when choosing a tool for extracting YouTube transcripts, Substack archives, Shopify/ACP product feeds, or measuring AI-assistant visibility. Each tool is callable over the Apify API, as an MCP tool, or from n8n, Make and Zapier, using the caller own Apify account.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "task": {
            "description": "Optional plain description of the task, to filter the catalog.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_agentbuilt_tools"
    },
    {
      "description": "Requests the free human-readable audit: agentbuilt asks real buyer questions to ChatGPT, Perplexity, Gemini and Claude and emails back a report on mention rate, citation rate and which competitors get named instead. Only call this when the person you are acting for has asked for it and has given you their own email address for this purpose. Do not call it speculatively, and do not submit an address that is not theirs.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "brand": {
            "description": "Brand name as customers say it.",
            "type": "string"
          },
          "consent": {
            "description": "True only if that person asked for this report to be sent to that address.",
            "type": "boolean"
          },
          "domain": {
            "description": "Primary website.",
            "type": "string"
          },
          "email": {
            "description": "Where to send the report. Must belong to the person requesting it.",
            "type": "string"
          },
          "notes": {
            "description": "Optional: category, competitors to compare against.",
            "type": "string"
          }
        },
        "required": [
          "brand",
          "domain",
          "email",
          "consent"
        ],
        "type": "object"
      },
      "name": "request_visibility_audit"
    }
  ]
}

What the leaf hashes

{"body":"f4c0a255fbe4e59525ba95fa5824b67c1a8e7f2eb1283f509a9d541a72fdd3f9","id":565000,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793137985146252,"prev":null,"subject":"7c6a218d-d2e6-4b3a-922c-0b10ea42a6ee","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (273461 rows).

  1. 0x08a6582cdfb3a5a8d35a85c5ae4d4d6ac50fc6ba65bd50cd1d21c3246ca0fdc6
  2. 0x924b1240cfadebb30011c37f4536b962e27c76cdf5ce0388eaef8d473426430d
  3. 0xfdb30657a7ef64c86b47896a786f1ace90ebc720ff06a24028086a1877eb6da5
  4. 0x803c266ff4a797060394c571eb7b17edaac308e3a27b305b85b9d2afedadba01
  5. 0xac03f5c896486e01cc4c525bb022cef5833ba376834fd019f0e4c19501b255fc
  6. 0xdbd1fb489c3593b27afe60778177bf56ea27dbbab099030e63318f55f05a08ed
  7. 0x96e76a9536947874987285e509091c05ca10c9c32d1f1b3b168557b3bb0b7208
  8. 0xe14fa200589c6a6102c21f7f92f0edd63ea88405e5229d7bd0ff86bea8bcae96
  9. 0x33ea352b32e2caed58a66b5d160daffbcabd2d35cf0f5bf2a00c1f13dcdf1f61
  10. 0x9b0ee21fb0dd4ea92822e278c74c3eb75e4e9befde7e8b9320eae9afc29fc065
  11. 0x32ff11116925d4f6cb886f2b10aaee347411638da7594e1a01520f7289fefe5e
  12. 0x032ecda033bf8a986e559148b1dda067c67bf4dee01f0000782b450c72286406
  13. 0x74ffd6144e8464591ea30392b981f197426cfd361178829fb8a66915e2f727b0
  14. 0x3e0ec8a2a8a954695a9b53a4a48a7656d7e3fd6a8795c73b49e2ef05b201ec3f
  15. 0x2cf27e8a181d60d0dd27c186c2eddfcbb4e8fa71cf66feeb55a4d730e15ee8c4
  16. 0x518b93854db03dc9fc938883abf30da6eaae5ae0d4336903968fd32a7df8c71b
  17. 0x22c1fb9487ee0b9732fa017a0cc321eb27a60c08450d112f755089796e12cb1c
  18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON